Commun. Comput. Phys., 7 (2010), pp. 904-926.

Investigation on Energetic Optimization Problems of Stochastic Thermodynamics with Iterative Dynamic Programming

Linchen Gong 1, Ming Li 2*, Zhong-can Ou-Yang 3

1 Center for Advanced Study, Tsinghua University, Beijing, 100084, China.
2 College of Physical Science, Graduate university of Chinese Academy of Sciences, Beijing, 100190, China.
3 Center for Advanced Study, Tsinghua University, Beijing, 100084, China; and Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing, 100190, China.

Received 24 July 2009; Accepted (in revised version) 8 October 2009
Available online 6 January 2010


The energetic optimization problem, e.g., searching for the optimal switching protocol of certain system parameters to minimize the input work, has been extensively studied by stochastic thermodynamics. In this work, we study this problem numerically using iterative dynamic programming. The model systems under investigation are toy actuators consisting of spring-linked beads with loading force imposed on both ending beads. For the simplest case, i.e., a one-spring actuator driven by tuning the stiffness of the spring, we compare the optimal control protocol of the stiffness for both the overdamped and the underdamped situations, and discuss how inertial effects alter the irreversibility of the driven process and thus modify the optimal protocol. Then, we study the systems with multiple degrees of freedom by constructing oligomer actuators, in which the harmonic interaction between the two ending beads is tuned externally. With the same rated output work, actuators of different constructions demand different minimal input work, reflecting the influence of the internal degrees of freedom on the performance of the actuators.

Notice: Undefined variable: ams in /var/www/html/issue/abstract/readabs.php on line 163
PACS: 05.40.-a, 82.70.Dd, 87.15.H-, 05.70.Ln
Key words: Iterative dynamic programming, stochastic thermodynamics, harmonic model.

*Corresponding author.
Email: (M. Li)

The Global Science Journal